Visual Content Analysis:
Notes on the 15th International Conference on Information Visualization, iV 2011
University of Northern Colorado, US
South Bank University, UK
This article comprises an overview of recent theories and applications in knowledge visualization and information visualization, which was compiled from the notes about the selected articles presented in the Proceedings of iV’11, the 15th International Conference on Information Visualization held in London, UK (Information Visualization Proceedings, 2011). This year about one hundred researchers, artists, and professionals from over twenty countries participated in the Conference. Contributors combined information visualization challenges with the interactive context and culture of knowledge visualization, and thus focused on complexity of data, information, and knowledge within many application domains. Issues selected for this overview, often describing cross-disciplinary projects, make a part of the wide spectrum of themes discussed at the conference. This overview comprises selected research and position papers on the visual content analysis applied to knowledge visualization domain, ontologies, visual thinking, information visualization theory and techniques, usability, evaluation and applications, visual analytics, visual data mining, digital art, and design visualization as an intersection of visualization, art, and design. The following text provides notes about selected themes: focus on knowledge visualization, semantic ontologies and the social web, visualization and digital art, information theory, applications, usability, and assessment, visualization – technical solutions, and visual interfaces for music selection.
Further works contributed to the Conference were focused on several other domains such as applications of graph theory, geometric modeling and imaging, geoanalytics, visualization in built and rural environments, cultural heritage knowledge visualization, biomedical visualization, and biomedical informatics. Models of information management addressed the data presentation, mapping, and temporal dimension issues.
The Symposium and Gallery of Digital Art: 2D Gallery, Movies/Animations, and Time-based Gallery accompanied the Conference. Artwork presented at the Symposium and Online Digital Art Gallery D-ART 2011 illustrates the article. Proceedings of the conference and art works presented at the D-ART Gallery can be seen online: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6003377 and
Knowledge visualization, web visualization, ontologies, visual thinking, information visualization theory and techniques, usability and evaluation, visual analytics, visual data mining, digital art, design visualization
Figure 1. Hans Dehlinger, T-Hof_March_2011-2x
(1) Focus on Knowledge Visualization
Visualization tools derive its form from many domains; moreover, there are no defined boundaries between different disciplines of visualization, while definitions and theoretical approaches change with the advances in technologies. In 2010 Masud, Valsecchi, Ciuccarelli, Ricci, & Caviglia identified the most important domains in visualization as:
- Data visualization – “information which has been abstracted in some schematic form” (Friendly & Denis, 2004) to provide visual insights in sets of data.
- Information visualization – “The use of computer-supported, interactive, visual representations of abstract data to amplify cognition” (Card, Mackinlay, & Shneiderman, 1999).
- Knowledge visualization uses visual representation to transfer knowledge, rather than data, between individuals.
- Scientific visualization deals with physically based data defined in reference to space coordinates, such as geographic data and computer tomography data of a body (Voigt, 2002).
- Information aesthetics forms a cross-disciplinary link between information visualization and visualization art.
- Infographics refers to tools and techniques involved in graphical representation of data, mostly in journalism, art, and storytelling.
Expert opinions about Knowledge Visualization were assembled at the 7th Int. Symposium on Knowledge Visualization and Visual Thinking accompanying the Conference (Bertschi, Bresciani, Crawford, Goebel, Kienreich, Lindner, Sabol, & Moere, 2011). Topics spanned from representation, storytelling, criticizing the lack of theory, communication, analytics for the masses, to trendy Visual Thinking and creativity beyond PowerPoint. Contributors agreed that visualization improves communication, as knowledge needs to be seen. They emphasized a process-driven concept of visualization, as without successful and sustainable transfer knowledge is meaningless. In the words of Stefan Bertschi, “the act of visualizing is more important than the image itself: medium>message.”
Tom Crawford (in Bertschi et al., 2011) reminds that the core of Knowledge Visualization is all about communication, with steps such as gathering, interpreting, developing an understanding, organizing, designing, and communicating the information. He suggests it is a recursive loop rather than a linear process. Our knowledge changes and with it changes the visual, which often provides so much insight that our knowledge changes and thus the visual also needs to change. Hence there is a need to re-think and redesign some of the most common forms of communication such as, for example, a recipe that has been unchanged for over 3,600 years. The recipe designer and a reader share a specialized language and process, if they have the same education or experience. For the purpose of knowledge visualization we would think earlier that a recipe contains four basic types of information: ingredients, process, and equipment combined with a series of techniques. However, the steps are often mixed. “By using the tools and process of Knowledge Visualization, we can begin looking deeply at the recipe’s components, who it is used by, and what they are using it for, and therefore create more effective tools that reduce errors and increase satisfaction. That is Knowledge Visualization” (pp. 329-330).
Figure 2. Jing Zhou, Worldnessness
Andrew Vande Moere (in Bertschi et al., 2011) states, ‘in order for information to transform into knowledge, one must share some context, some meaning, in order to become encoded and connected to preexisting experience. In that sense, Knowledge Visualization, which is recognized as an independent discipline (Burkhard, 2005), can be considered data visualization ‘in context.’ With an attempt to unravel the driving principles that influence the trends, patterns, and outliers in data, data trends can be explained, rather than simply discerned. Vande Moere indicates that stories are powerful means of providing context in interpreting the overreaching meaning.’ Visual storytelling exists in the domains of online journalism, graphic design, comics, business, art, and visualization research (Segel & Heer, 2010). According to Vande Moere, “the emerging popularity of online visual storytelling (Schmitt, 2009) presents at least two new challenges.” First, on a phenomenological level, while visual storytelling techniques have the ability to direct a viewer’s attention through a sequential narrative, or a series of visual transitions, there is a need to explore how the context, which drives the data-driven knowledge acquisition, is best represented. “Second, it might be equally revealing to analyze visual storytelling techniques in the context of Knowledge Visualization, or vice versa, investigate Knowledge Visualization design methods.” With the “emerging popularity of data visualization in current online media, expectations will inevitably shift from simply delivering information to conveying the causally influencing factors that drive the events in our world today” (pp. 330-331).
Randy Goebel (in Bertschi et al., 2011) stresses the diversity of ideas about transformation from data to pictures and rendering objects in a visual space, “articulation of insight into visual semantics and the role of cognitive science in drawing inferences from pictures.” Since there is no theory of visualization, scientific interest in visualization would provide “a disciplined assessment of the quality of visualization techniques. … If the simply stated goal of visualization is to amplify the human visual system’s ability to draw inference from complex data, then we need much more work on what kinds of inferences can be made, and how well they can be made. … It is scientifically useful to view pictures as inductive inferences about the data and data relationships from which they arose … evaluate the quality of inference that a visualization method provides. … develop scientific discipline about how to assess alternative visualization methods” (p. 331).
Sabrina Bresciani (in Bertschi et al., 2011) states that Knowledge Visualization ‘means mapping concepts graphically, by structuring text and visuals in a meaningful way. … examples include conceptual diagrams, knowledge maps, visual metaphors and sketches.’ Dual coding theory – Paivio, 1969. ‘Images have an impact also on the emotional attitude of the user, by providing engagement and motivation. Knowledge Visualization is ‘useful for collaborative work: mapping the group dialogue can facilitate the integration of knowledge… offer insights to the user… Knowledge Visualization poses a stronger emphasis on knowledge and experiences rather than on numerical information. … A map drawn with pen and paper is a common example of Knowledge Visualization, which is not computer generated. … Future directions of development for Knowledge Visualization’: 1. Studying and measuring the impact of Visualization, especially in emerging forms of collaborative interactions, including visual groupware, Group Support Systems, and social media. 2. Input devices such as multi-touch screens provide fluid forms of interaction. 3. Testing Knowledge Visualization in new domains such as intercultural communication (to overcome linguistic and cultural barriers).
Figure 3. Dena Elisabeth Eber, Mikveh 1
Wolfgang Kienreich (in Bertschi et al., 2011) stresses, “Knowledge Visualization is a missing link between expert tools such as Visual Analytics and the frantic demand of the general public for intuitive ways to cope with personal digital universes. Visual Analytics, the science of analytical reasoning facilitated by interactive visual interfaces, combines automated analysis, visual representations, and user interaction in a close loop intended to provide users with new insights (Thomas & Cook, 2006). … Visual Analytics emphasizes the use of visual abstractions to represent aggregated information and facilitate the formulation and validation of hypothesis by expert analysts (while) Knowledge Visualization emphasizes the use of visual metaphors, facilitates collaborative dissemination and decision making by domain experts.” Personal digital universes (photo collection, etc.) require multimedia search and retrieval techniques. Personal social network requires methods of social network analysis. The author proposes that “Visual Analytics and Knowledge Visualization join forces for analyzing, evaluating and, ultimately, utilizing the wealth of knowledge thus created” with multi-touch surfaces as a driving technological factor for a closer integration. Visual Analytics could contribute techniques for the automated analysis of large amounts of information and the closed loop approach with analysis, visualization, and interaction,” (pp. 332-333), e.g., with user feedback for consumer sentiment and product quality on a personal level. Knowledge Visualization – contributes design and user specific visual representations, e.g., with a map, meter, or aquarium metaphor for users with limited visual literacy.
Vedran Sabol (in Bertschi et al., 2011) defines knowledge as “an acquired, established set of facts, recognized to be valid and valuable within a specific domain.” He describes data as “sequences of numbers or characters representing qualitative or quantitative attributes of specific variables. To obtain information, data is processed and brought into a context within which it gains a specific meaning and becomes understandable to users. Information visualization makes use of human visual perception capabilities for recognition of patterns and extraction of knowledge from raw data and information. Visual Analytics builds upon Information Visualization to facilitate analytical reasoning by combining automated discovery and interactive visualization” (Thomas & Cook, 2005). “While Visual Analytics targets analysts in application domains such as business intelligence, Knowledge Visualization deals with expression and creation of knowledge, targeting areas such as knowledge management and strategic management in general. … Both fields share several common properties: they breed new knowledge, deliver support for decision making, and provide a common basis for collaboration” (p. 333).
Figure 4. Chiara Passa, From the series “Live Architecture”: “Speaking at the wall”, 2008. Interactive video installation.
According to Martin Lindner (in Bertschi et al., 2011), Visual Thinking as a new trend in the age of ‘micro–web’ started in the 1990s: digital data, Apple-driven graphic engines, and the Web 2.0 resulted in a doodle revolution. With reference to past events, Otto Neurath coined the term ‘infographics’ around 1930. Morville’s (2010) presentation about visual thinking, the new way of using Power Point by David Byrne, a wave of making doodles and napkin sketches, all caused that new visual languages and new cognitive styles were evolving toward the micro-media convergence. “Because they only require a small attention span to get their ideas and messages, these simple user-generated objects can be easily circulated in the cloud: in blogs, via flickr, SlideShare, or YouTube. This is part of a paradigm shift from ‘published ideas’ to ‘circulating ideas (and) collaborative thinking enabled by the Web 2.0 ecosystem.” Companies such as Enterprise 2.0: Building Social Business (2011) and Root Learning (Haudan, 2008) adopt visual thinking as a main trend. An animated graphic recording video (for example, Johnson, 2011) may exemplify “the natural format for the hive mind” (pp. 333-334).
Stefan Bertschi (in Bertschi et al., 2011) states that strategic and operational processes rely on operation and interaction, planning, implementation, project and change processes (Burkhard, 2005). “Knowledge Visualization aims to understand how the sender’s intended meaning can be transferred in such a way that it is not distorted in the recipient’s perception, therefore allowing effective and efficient communication to take place. … For most people we may state that complex dependencies and interactions can more easily be understood when illustrated: an intelligent process flow chart makes more sense than a numbered list describing the same process in words.” The author stresses that visual thinking helps to make best use of the understanding of others, and advises, “Draw and sketch in front of a live audience, or even better, sketch collaboratively. … Speaking and listening with your eyes also means making full use of the available methods” (see Lengler & Eppler, 2007, Periodic Table of Visualization Methods). According to Bertschi, visualization improves communication, in particular the interaction around cognitive processes. “Visuals stimulate discussion, and discussion creates knowledge” (pp. 334-335).
Figure 5. Aaron Oldenburg, After – videogame
Martin Eppler (2011) describes the domain of knowledge visualization as “a relatively young discipline that focuses on the collaborative use of interactive graphics to create, integrate and apply knowledge – particularly in the management context. This emerging approach nevertheless builds on decades of research on using images collaboratively for sense making and knowledge sharing” (Eppler, 2011, pp. 349-353). The author defines knowledge visualization (in contrast to the mostly data-driven information visualization field) as follows: knowledge visualization designates all (interactive) graphic means that can be used to develop or convey insights, experiences, methods, or skills (Eppler & Burkhard, 2004, Eppler & Burkhard, 2007). The author reviews seminal concepts from different disciplines that help to explain how visualizations can effectively act as collaboration catalysts and knowledge integrators. His review “makes it apparent that many different labels and conceptions exist in very different domains to explain the same phenomenon: the integrative power of visuals for knowledge-intensive collaboration processes. These concepts can be used to compile a list of the requirements of an effective knowledge visualization.”
Eppler reviews seminal concepts related to knowledge visualization coming from different domains, that include, among others, the principle of Visual Variety that uses Elkins’ (1999) idea of Visual Hybrids (a graphic notation system that combines visualization formats such as graphs, charts, tables, diagrams, genealogical trees, etc.), Tufte’s (1997) concept of Confection (an assembly of many visual events, selected from various streams of a story, then brought together), and Latour’s (1990) notion of Immutable Mobile (that emphasizes the need for visual variety defining such artifacts as consisting of figures, diagrams, plates, texts, silhouettes). The author introduces then a principle of Visual Discovery as detecting new patterns, both in knowledge visualization and information visualization. In information visualization insights are generated not out of analysis and mapping of mass data, but rather visualized individual and collective views, opinions, assessments, and analyses. The concept of Diagrammatic Reasoning (Peirce in Hoffmann, 2003), a think tool, for example for the positioning of elements according to their similarities in overlapping or containment circles, as in a Euler of Venn diagram. With the principle of Visual Guidance images are used as representations of data but also as catalysts for a collaboration process (images as signposts to what should be discussed). The concept of Representation Guidance (Suthers, 2001) refers to e-learning. The new concept of Visual Playfulness relates to the Eden and Ackermann’s (1998) notion of Transitional Objects. The author concludes the paper by using the concepts to compile a list of the requirements of effective knowledge visualization and showing the theoretical and practical implications derived from five principles:
- Visual Variety – visual vocabulary to express ideas through various ways
- Visual Unfreezing – of captured and frozen visuals to be re-elaborated and changed again
- Visual Discovery – connecting elements in new ways and detecting new patterns
- Visual Playfulness – inviting to change perspectives, assume new roles, immerse in the collaborative effort, and reframe issues creatively
- Visual Guidance – providing a clear ‘roadmap’ of how it should be iteratively populated or completed.
Figure 6. Anna Ursyn, Micro - Macro
(2) Semantic Ontologies and the Social Web
Gkoutzis and Geroimenko (2011, pp. 205-210) describe the Semantic Web “as a method of interrelating information to help computers derive conclusions based on the links between data. With the rising popularity of Social Networks though, unconnected pieces of information have only chaotically increased instead of becoming parts of well-organised Taxonomies.” The authors “suggest a system which will take advantage of the Social Web and put it to work so that it will operate under the common cause of categorizing old and new data into an unlimited Semantic Ontology. This ontology will be created gradually and ever-changing, like a versatile encyclopaedia of information compiled from interconnected data. With the addition of a 3D Web interface on top of the ontology management mechanisms, the entire experience will become more user friendly, providing graphical presentation of all opinions and interpretations in a clear and comparable manner.” The Semantic Web, introduced in 1999, helps computers derive conclusions based on the links between data. With Social Network, unconnected pieces of information do not become parts of well-organized Taxonomies. An unlimited Semantic Ontology uses the Social Web to categorize old and new data. With the addition of a 3D Web interface on top of the ontology management mechanisms, the ontology is ever changing. “The entire experience becomes user friendly, providing graphical presentation of all opinions and interpretations in a clear and comparable manner.” XML and technologies based on it such as the Semantic Web provide facilities for electronic devices of a different nature to communicate with each other and exchange data in a commonly acceptable way. The Semantic Web is trying to organize information into standardized structures called Ontologies. Social Networks can benefit from the use of Semantic Ontologies, to improve their simple method of tagging, which is based on keywords rather than logical concepts. Adding Semantics can prove profitable in the quality of search results and in data categorization. It can result into a powerful online tool for Social and Gaming worlds.
Search engines and the Semantic Web. Gkoutzis and Geroimenko state that computers are programmed by people to respond in a predefined way to specific actions. They follow the rules but cannot yet cross the line from computing to improvising (coming up with original ideas). Search Engines are precise, based on mathematical formulae for text searching, but the meaning is totally lost, so they provide links to too many various things. The Semantic Web is aimed to help computers understand information by using the relations between interconnected objects: by grouping information into Ontologies, logically organized datasets, a formal version of Taxonomies (Pidcock, & Uschold, 2003). Several Semantic Web based Search engines already exist, such as Swoogle, semantic web search (2007) and Hakia (2010). They match a typed text to ontology items (based on logical connections derived from the item meaning) rather than just plain keyword relevance. Ontology standardization and the resulting information categorization will provide well-organized data to the scientists, musicians, and the Social Web communities.
The power of Social Networks. According to Gkoutzis and Geroimenko, in 1990s users created personal websites, and companies were giving away Web space for free placing advertisements on top of each webpage. Users began interact by linking websites, exchanging awards, guest-books, publishing and thus creating a new global village. At the end of 1990s users called their personal websites blogs, and in early 2000s created “online social networks,” called by Tim O’Reilly “Web 2.0.” Social network prompted users to upload inside a personal profile page (no more free space). Friendster, Facebook, LinkedIn became Social Web giants, and then YouTube, Flickr, and Delicious. They all use Folksonomies for classification with tags (good or not-so-good). When the Social Web will merge with the Semantic Web, the semantics have been agreed upon, and data sharing will be seamless and instant, with annotated data instead of plain old keywords. Visualization techniques may help to annotate data.
3D environments and Virtual Worlds. Gkoutzis and Geroimenko describe how computers had first the text command interfaces, then also they were able to present graphics. 3D graphics improved the games, which first offered first point-and-click, and then 3D gaming. First they displayed first-person shooters, then massively multiplayer online role-playing games. With the Social Networking niche in mind, companies combined 3D gaming environments with online communities, such as Second Life, Active Worlds, and IMVU, among others. Google Lively also tried to combine browser based 3D graphics with a social network.
The Future of Web: Social, Semantic, and 3D, as seen by Gkoutzis and Geroimenko: The merging of the Social Web with the Semantic Web is inevitable. The authors propose a system with the properties of the Social Web, with 3D Web Interface on top and Semantic Ontology behind it. The advantages of 3D Social Community are 3D avatars and personalized virtual ‘lounges’, a source of knowledge. It all creates an information driven community with the user friendly 3D Web interface, for example, when one looks for a ‘Person’ who is working for a ‘Business’ in a specific ‘Location.” Social semantics drawbacks may be related to human responsibility, credibility, and objectivity. Metakosmos will be a 3D Social Web community that stores info with Semantic Web Ontologies.
Figure 7. Watsatree Diteeyont, Change
In a paper “Using Visualization for Exploring Relationships between Concepts in Ontologies” Siqueira da Silva and Dal Sasso Freitas (2011, pp. 317 - 322) discuss a visualization tool for exploring relationships between ontology concepts. The authors indicate that ontologies are usually represented as static 2D graphs. The relationships exhibited as overlapping edges may cause a cognitive overload. On the other hand, 3D representations can also lead to confusion in terms of navigation due to occlusion. Moreover, as the ontologies grow incorporating new concepts (and their relationships), the visualization complexity increases either in 2D or in 3D. The authors designed a visual and interactive method for exploring ontologies, improving the process of insight from such data (2.5D visualization). In a visualization tool, the authors employ linked tree structures that capture the hierarchical feature of parts of the ontology while preserving the different categories of relationships between concepts. Ontologies are displayed as trees on a plane, representing only the hierarchical relationships between concepts, allowing the user to explore other connections by creating projections of nodes (concepts) in another plane and linking them according to the relationships to be analyzed.
H. Paul Zellweger (2011, pp. 323 - 328) describes “Knowledge Visualization of Database Content Created by a Database Taxonomy.” Information has to be pre-structured. All technologies have an underlying mathematical core (Burgin, 2001). “Information Visualization focuses on assigning meaning to raw data and on the use of computer-supported representations of abstract data to amplify cognition (Card et al., 1999). Knowledge Visualization places emphasis on a more encompassing phenomenon, namely, interaction with the receiver (Burkhardt, 2005). As Bertschi (2007) says, Knowledge Visualization lacks a rigorous theoretical foundation. Information Visualization is inefficient in displaying big abstract data sets, as well as concept mapping, as it relies on a single visual plane. The synergy between information visualization and knowledge visualization is explored using the "Database Taxonomy" to guide the way. The paper draws on Burgin’s mathematical theory of Named Sets, a fundamental BNS triad (1990): two components are bound together by a third element, a consistent set of ‘rules’. The new knowledge visualization treats all the database content as if it were scientific data, regardless of the database application. The new type of Knowledge Visualization is the Database Taxonomy, which pre-structures relational data in a database. The author models the logical space of the data and data relations in a more abstract fashion. This visualization technique uses recursion to transform raw data into information and then into knowledge. The graphics that display this taxonomy include industry standard interfaces, such as nested list menus and tree views, as well as custom-built displays. This mathematical tool penetrates deep into the logical structure of data and data relations, enabling a single algorithm to generate a conceptual knowledge structure, which pre-structures raw data in the database into a list of nested data-topic lists that works like a book index. For end-users, this visualization is familiar, convenient and precise. For the research community, this knowledge structure and the techniques used to build it offer an empirical tool for investigating the underlying properties of data, information, and knowledge on a computing device. The transformation from data to information to knowledge is automatic and seamless, thanks to a novel analysis of the logical structure of the symbols on these mechanical devices, one which reveals meta-symbols consisting of physical values (v) and constructed-types (t). The Database Taxonomy also provides a first glimpse into how navigating this structure can generate a predicate logic expression, an outcome which the author believes promises to advance our theoretical understanding of knowledge visualization and of the influence of a digital media on symbolic logic.
Figure 8. Kaz Maslanka, The Empty Paradox
(3) Visualization and Digital Art
In a paper “Art, Interaction and Engagement” Ernest Edmonds (2011, pp. 451 - 456) reviews the development of frameworks for thinking and talking about interactive art in the context of the author’s personal practice over the last forty years: from a simple direct notion of interaction to communication between people through art systems and, more recently, interactive art for long-term engagement. Concepts evolve over several dimensions together with the practice of interactive art. The author explores interaction of form, language, and logic in art that involve shapes, color, and words (names for hue, saturation, and intensity). Interactive art systems that involve artifacts and audiences became complex and went from reaction to influence over time (as in HCI). With devices given to the audience, approaches to interaction can be termed direct, facilitated, or ambient, while engagement, in the author’s practice, can be called attracting, sustaining, and relating.
Francis F. Marchese (2011, pp. 395 - 402) considers in a paper “Exploring the Origins of Tables for Information Visualization“ the deep history of tables as visualization modalities. It covers four kinds of tables that have appeared between 1900 BCE and 1300 CE: Sumerian accounting tables, chronicles, canon tables, and medieval calendars as representations of some of the earliest milestones in information visualization. Analysis of these tables demonstrates as early as 1300 BCE the need to visualize information had driven the invention of representations that transformed the way information has been communicated and used.
Marquis & Wyeld (2011, pp. 585 - 587) highlighted the role of contemporary media in recasting this culturally significant work in a new light. They discussed the contemporization of Dante's Inferno in the form of a computer game. More accessible to the current generation, the contemporization of Dante's Inferno loses none of its impact and meaning. More than this, the game facilitates the search for a virtual soul-space previously reserved only for those vested with the 'given powers' (in Medieval times and prior). In this sense, the contemporization of the Inferno also brings with it much of the mythological intensity it once sought.
David Hockney's (2001) book “Secret Knowledge: Rediscovering the Lost Techniques of the Old Masters” reignited the debate on the use of optical devices for constructing perspective images in the Renaissance. Hockney brings his insights as an artist to the debate. In a paper “The Implications of David Hockney's Thesis for 3D Computer Graphics“ Theodor Wyeld (2011, pp. 409 - 413) explores the Hockney’s thesis in terms of its implications for 3D computer graphics. Just as technology informed the Renaissance artist on ways of seeing and representing natural phenomena, 3D computer graphics today uses algorithms to simulate these same phenomena. For both, various techniques are used to make the images produced seem real or at least real enough. In the case of the Renaissance artist, painterly techniques were used to generate the illusion of clarity. For 3D computer graphics, mathematical algorithms are used to simulate many of the same effects. Striving for realism is a common theme. However, while the Renaissance artist never lost site of their role in interpreting what they see, 3D computer graphics is supposed to be underpinned by the certainties of its apparent scientific veracity. But is this certainty deserved or is it merely that science and art are intertwined in ways that mean one is reliant on the other?
Figure 9. Vladimir Geroimenko, Dartmouth-Devon
According to Vladimir Geroimenko (2011, pp. 461 - 464) digital photo painting is a newly emerging artistic and cultural phenomenon in both fine art and everyday life. The latest versions of specialist software, such as Corel Painter or Adobe Photoshop, allow anyone to turn their selected photographs into enchanting paintings, produced in any style desired. The first book on this subject “The Art of Digital Photo Painting” by Marilyn Sholin was published in 2009. Photographs provide visual references to inform and inspire artists in their work. In accord with Hegel’s dialectic method, the author sees transition from quantity of digital photographs to new quality of digital painting. When printed, digital paintings are physical, material and exhibited in galleries. Originality is a question, and what can we classify as original? Everyone can try to be an artist. The author explores the conceptual, creative and cultural aspects of turning photos into paintings using popular software and plug-ins. He argues that the mass production of original digital paintings and fine art prints may signal a new era in the relationship between photography and painting, and discusses why digital photo painting might be the 'next big thing' in digital art and become a new hobby for millions.
Figure 10. Gabriele Peters, Seite 36
(4) Information theory
Andrew P. Lucia, Jenny E. Sabin, and Peter Lloyd Jones (2011, 379-388) explored dynamic organizations of matter in the multi-dimensional, microscopic-scale human cellular systems and the human-scale perceptual environments. In terms of the information theoretical framework, this study span architecture and the biological sciences and examines latent virtual diagrams residing within real dynamic material systems. The authors examined the systems’ generative potential that emerges from difference, history, and the structural information content of spatiotemporal data arrays. A design tool developed by the authors offers a method for visualizing the underlying formal structures of these data arrays, and analyzing dynamic biological data sets to determine spatiotemporal behavior in different cell types within cellular environments. In architecture and design, such analyzes relate to questions “how we conceive of (to design) and construct (to build) the world about ourselves. … Such area is explored in the biological sciences through the examination of cellular motility in relation to its surrounding architecture or extracellular matrix environment. Education, technology, and traditions of the trade frequently predispose architects and designers to approach the world via descriptive and projective geometric principles.” The alternative mathematical formal abstractions and representations allow investigating the topics of materiality and affect. The authors ask, can a dynamic material system’s characteristics be understood in terms of spatiotemporal order, difference, and information rather than through descriptive or projective geometric terms, and how actual morphologies and their perceptions could be represented in architectural design? Here, information is defined as a function of temporal difference within a particular signal(s) within a specific spatial neighborhood (rates of change). Seeing difference makes a shift in the way we relate to objects that generate a continuum of constantly fluctuating potential information arrays. Information is the medium of communicative exchange for relative observing bodies, organic or inorganic. Each observer possesses memory or history that has an impact on the instantaneous perception about its environment (information entropy – the quantity of information received is equal to the reduction in entropy – Kenneth Norwich, 2003). James J. Gibson (1986) developed a theory of perception based upon ambient information arrays. From a design standpoint, a parallel aim of this research deploys these same information theoretical principles as an analytic technique, specifically in areas of generative design, materiality, and affect as they pertain to organizations of data arrays generated from objects within their environments with and without perceiving subjects, called here the relative observers. The authors measured difference (discrete pixels intensities across all time states within a video) – fluxes of matter and energy to generate potential information by mapping image difference analysis, in case studies, of vascular smooth muscle cells, and spatial perception of an observer through a hallway. They also measured perception of spatial density distribution, pixel brightness, and intensity mapping for objects and environments (Gaussian curvature analysis).
Graphs, generally used as data structures in computer science applications, have steadily shown a growth in mapping various types of relationships, from maps to computer networks to social networks. As graph layouts and visualizations have been at the forefront of graph drawing research for decades, it consequently led to aesthetic heuristics that not only generated better visualizations and aesthetically appealing graphs but also improved readability and understanding of the graphs. A variety of approaches examine aesthetics of nodes, edges, or graph layout, and related readability metrics. Amalia Rusu, Andrew J. Fabian, Radu Jianu, & Adrian Rusu (2011, pp. 488 - 493) focused on the edge crossing problem and proposed the incorporation of the Gestalt principle of closure to alleviate the Edge Crossing Problem in Graph Drawings. To improve graph aesthetics and readability, they introduced the concept of breaks in edges at edge crossings. A break is a gap in an edge drawing occurring in the vicinity of an edge crossing. At every edge crossing, one of the incident edges is broken, which will prevent any unintentional Gestalts that occur at edge crossings that reduce the readability of a graph drawing. Preliminary results and user studies show that this technique could play a role in improving graph readability.
Categorical data is common within many areas and efficient methods for analysis are needed. It is, however, often difficult to analyze categorical data since no general measure of similarity exists. One approach is to represent the categories with numerical values (quantification) prior to visualization using methods for numerical data. Another is to use visual representations specifically designed for categorical data. Although commonly used, very little guidance is available as to which method may be most useful for different analysis tasks. Sara Johansson Fernstad and Jimmy Johansson (2011, pp. 80 - 89) present a task based performance evaluation of visualization approaches for categorical data analysis. The authors compare the performance of employing quantification prior to visualization and visualization using a method designed for categorical data. They also provide a guidance as to which visualization approach is most useful in the context of two basic data analysis tasks: one related to similarity structures and one related to category frequency. The results strongly indicate that the quantification approach is most efficient for the similarity related task, whereas the visual representation designed for categorical data is most efficient for the task related to category frequency.
Figure 11. Liz Lee, Obsession
(5) Applications, Usability, and Assessment
The use of visualization is a superior strategy in the communication of business tactics. In an experimental study (Kernbach & Eppler, 2010) managers who were exposed to visualization in the form of visual metaphor and roadmap paid significantly more attention to the strategy, agreed more with the strategy and recalled the strategy better than did subjects who saw text in the form of PowerPoint. Those exposed to visualization in the form of visual metaphor and roadmap perceived the visual and the presenter significantly better than did those subjects who where exposed to text in the form of PowerPoint. According to Sabrina Bresciani, Martin Eppler, Asha Kaul, & Riina Ylinen (2011, pp. 365 - 370), “visualizing knowledge means mapping concepts graphically, by structuring text and visuals in a meaningful way… for enhancing both the cognitive and emotional response to the presented content” by creating involvement and engaging employees. As the authors state, “in recent years we are witnessing a growing interest and use of knowledge visualization for communicating ideas and insights. Companies are deploying diagrams and knowledge maps to convey crucial business concepts. Scholars are reporting successful company cases, theorizing on the topic and compiling classifications and best practices. Yet few studies have attempted to prove the effectiveness of visualization, or have they based their hypotheses on theories with predictive power. We aim to provide a contribution for the advancement of the field of knowledge visualization by testing the effects of different visualizations on the attitude toward its content. Second, we assess if visualization effectiveness is universal or culturally-bounded.” Visual representations are used to organize information and concepts in order to convey knowledge, to amplify cognition and to enhance communication. Examples include conceptual diagrams, knowledge maps, visual metaphors and sketches. A map drawn with pen and paper is a common example of Knowledge Visualization that is not computer generated or interactive. Bresciani et al. indicate, “images have an impact also on the emotional attitude of the user, by providing engagement and motivation. Visualizing knowledge is useful for collaborative work: mapping the group dialogue can facilitate the integration of knowledge.” The common aim of Knowledge Visualization and Information Visualization is to offer insights to the user. However, Knowledge Visualization poses a stronger emphasis on knowledge and experiences rather than on numerical information. The authors conducted an experimental study, comparing text and two knowledge visualization types: a timeline for the Westerners (a sequential and abstract diagram) and the mountain trail for Asians (a holistic and metaphorical representation). The results of 231 subjects in Europe and India demonstrate that knowledge visualization has the power to increase the effectives of the message compared to text, and that these benefits replicate across different cultures. Communicating a business strategy with knowledge visualization, compared to text, has a significant positive impact on the cognitive and on the emotional response of the subjects. As stated by Bresciani et al., future directions of development for Knowledge Visualization include: (1) Studying and measuring the impact of Visualization, especially in emerging forms of collaborative interactions, including visual groupware, Group Support Systems, and social media. (2) Providing fluid forms of interaction with software and particularly in groups with the use of input devices such as multi-touch screens. (3) “Introducing and testing Knowledge Visualization in new domains, including for instance intercultural communication, a context where visual representations can be particularly useful to overcome linguistic and cultural barriers.”
Figure 12. Cris Orfescu, Transparence 1
On the basis of a large corpus of wine reviews, Andreas Kerren, Mimi Prangova, & Carita Paradis (2011, pp. 135 - 144) propose a range of interactive visualization techniques that are useful for linguistic exploration and analysis of lexical, grammatical, and discursive patterns in text. The authors combined approaches according to Shneiderman’s mantra (1996); they used a scatterplot, bar charts, histograms, text visualization (word tree with a root, tags and words, tag clouds), and world map visualization. Their tool for visualization of sensory perception descriptions allows linguists and others to make comparisons of visual, olfactory, gustatory, and textual properties of different wines from different parts of the worlds, from different grape varieties, or from different vintages. It also supports the immediate creation of visual profiles for descriptions of sensory perceptions for exploratory purposes as well as for purposes of confirmatory investigations of linguistic patterns in text and discourse and their correlations to metadata variables.
Wibke Weber and Ralph Tille (2011, pp. 343-348) examined the use of visualizations in corporate presentations. Results showed that the executive managers did not know the design principles or effective visualizations. The authors interviewed executive managers of a leading technology company about how they create business presentations, and focused on which visualization types they use and whether they would accept new forms of visualizations such as information graphics. The most popular visualization types managers use in presentations are bar and pie charts. The term "information graphic" is not known. The authors’ concluded, “If a company wants to change or improve its communication, it will have to become aware of the power of visual storytelling and start an ‘iconic turn’."
Figure 13. Teja Krasek, Twin Star
A paper “Contract Clarity through Visualization – Preliminary Observations and Experiments” by Helena Haapio (2011, pp. 337 - 342) presents preliminary observations of research work in progress, aimed at developing new methods to improve the clarity and usability of commercial contracts. In the crafting of commercial contracts, many participants are involved, often professionals from different countries and backgrounds. The challenge, then, is to achieve a balance between the business and legal requirements and to facilitate communication and coordination. While some contracts may need to work as evidence in court, most contracts do not. Instead, they need to work as business tools for the parties so they get the results they want to accomplish. In the move from goods to services and solutions, contracts are part of companies’ value creation. Haapio proposes a new field of research and practice, contract visualization, and invites cross-professional dialogue to explore the opportunities that exist for industry-changing innovations in this area.
Yvonne Eriksson, Peter Johansson, & Petra Björndal (2011, pp. 403-408) stress the advantages of showing action in pictures: “One challenge for the global market is to overcome communication problems of different kinds. The largest communication problem is language; people speak different languages and have limited knowledge in other languages. This problem is central in manuals and instructions for assembly and installations. One hopeful solution is that pictures can replace verbal instructions. In this paper we will discuss how illustrations in flat perspective can be useful for showing action in drawings.” Even small products are “accompanied with big instructions in several languages that may weigh more than the product itself. The substitute for written instructions is visual instructions. However, to replace language with pictures is complex, since language and pictures belong to different symbol systems, and therefore demand different strategies from the designers of instructions. The goal is to overcome differences in cultural traditions and to focus on the actual action rather than the object itself.” It is necessary to disambiguate instructions. Pictures are often of poor quality, photos are overloaded, CAD files are complex and made for different purposes. Engineering drawings that come from French encyclopedists (Jean le Rond d’Alembert) and James Diderot (Barthes, 1964) are difficult for China people because they use instrumental pictures coming from the 13th century.
Figure 14. Lane Last, Maya
(6) Visualization – technical solutions
Dinh Quyen Nguyen, Christian Tominski, Heidrun Schumann, & Tuan Anh Ta (2011, pp. 32–39) describe design strategies for visualizing spatially and temporally referenced tags similar to tag clouds on maps. The authors state, “Nowadays, a great amount of data is created and distributed on the Internet. Tagging has become common practice to structure these data for easy access. Often the data and the associated tags contain spatial and temporal information. Temporal information of tags is encoded through the visual appearance of text or through additional visual artifacts associated with the tags, whereas the location of tags on a map illustrates the spatial references.” The authors demonstrated a solution based on an interactive visualization prototype for the exploration of both spatial and temporal references of Flickr tags.
Serge Gebhardt, Christine Meixner, & Remo Aslak Burkhard (2011, pp. 355-358) describe in a paper “Distributed Group Collaboration in Interactive Applications” approaches for near-real time collaboration over distance in interactive applications: a browser-based, bi-directional, client-server network communication, concurrent object manipulation, and data synchronization using five multi-touch displays. Two distant users may not manipulate the same object at the same time, so there is a token per object and the server registers the association. For security reasons applications running in web-browser are generally not allowed to open generic network sockets. Browsers have to use the standard HTTP protocol only. The authors implemented the HTTP Duplex Channel technique, which gives an illusion of a bi-directional channel, likewise to a generic socket. They present approaches to tackling most of the encountered challenges by using their interactive risk management tool as an illustrative example. They focus on browser-based bi-directional client-server network communication, concurrent object manipulations, and data synchronization.
Figure 15. Ina Conradi, Torment, study on perceptions of emotion provoking images
It is not very intuitive to manipulate objects visualized in 3-dimension by a mouse, because a mouse can only move in 2-dimension space. Mariko Sasakura, Akira Kotaki, & Junya Inada (2011, pp. 429-433) propose a 3D molecular visualization system with mobile devices, an interaction technique to manipulate 3D objects by mobile devices with acceleration sensors. They have implemented an interaction technique using 3D acceleration sensors of mobile devices: developed a 3D molecular visualization system by using a library for using acceleration sensors, so the system displays results of a simulation of the molecular dynamics method. In the system, they can rotate 3D objects by leaning a mobile device and change a viewing location by moving a mobile device.
In the realm of computer graphics, methods used to control a user's point of view in a three-dimensional world are rather convoluted and are often tightly coupled to the rendering system used. In response to this issue, Adrian Rusu, Spence DiNicolantonio, Robert Russell, & Eric Velte (2011, pp. 434-439) have developed an abstract camera controller for 3D visualizations – a system that provides an intuitive interface for visualization and simulation programmers, while removing renderer dependencies completely. This system follows common object oriented design principles to encapsulate complex mathematics and computations involved in synthetic camera manipulation, providing a foundation for high-level camera features such as a programming interface for information visualization application. Using the camera by students with no graphics experience and developing visualization system using the camera controller provided assessment of this abstract camera controller system for 3D visualizations.
Figure 16. Carol Flaitz, Micron Opus
The evolution of mobile devices, especially the integration of sensors, is fostering the development of context aware visualization applications. The adaptation to usage contexts is crucial to overcome the diverse limitations that exist in a mobile device, namely the screen size. However, most of the currently developed applications focus on specific contexts. Paulo Pombinho, Ana Paula Afonso, & Maria Beatriz Carmo (2011, pp. 151-157) propose a Chameleon – a context adaptive visualization framework for a Mobile Environment that has the goal of enabling the development of applications that use a diverse set of contexts and adaptation methods.
Hui Wei, Enjie Liu, Xia Zhao, N. J. B. McFarlane, & G. J. Clapworthy (2011, pp. 632-637) focused on the biomedical area when they proposed an easy way to perform a Web-based 3D visualization for biomedical applications, which accepts two data resources, local and remote, as input and copes with two types of algorithm, built-in and remote. Web technology makes it possible to use software maintained on a remote server. This approach provides a virtual client environment, in which users can employ remotely installed software interactively using any standard browser. The proposed approach is a generic one and can be used in many other application areas.
Figure 17. Wes Thorpe, Concert
(7) Visual interfaces for music selection
Several authors presented techniques aimed at creating visual interfaces for music selection. Wakako Machida & Takayuki Itoh, (2011, pp. 145-150) created “Lyricon: A Visual Music Selection Interface Featuring Multiple Icons.” Lyricon is a technique that automatically selects multiple icons of tunes block-by-block, and effectively displays the icons. Lyricon selects icons based on musical features and lyrical keywords. In other words, Lyricon can reflect not only the features of the tunes but also the story of lyrics on its icon selection. Users can understand both impression of the sounds and the content of the lyrics, and they can choose songs, which is suitable for their feeling based on visual impression of the icons. Besides, embedding Lyricon on GUIs of music players is convenient to play specific parts of songs.
Yuri Saito & Takayuki Itoh (2011, p. 426) presented “MusiCube: A Visual Interface for Music Selection Featuring Interactive Evolutionary Computing.” The authors state, “We often want to select tunes based on our purposes or situations. For example, we may want background music for particular spaces. We think interactive evolutionary computing is a good solution to adequately recommend tunes based on users' preferences. This paper presents MusiCube, a visual interface for music selection. It applies interactive genetic algorithm in a multi-dimensional musical feature space. MusiCube displays a set of tunes as colored icons in a 2D cubic space, and provides a user interface to intuitively select suggested tunes. This paper presents a user experience that MusiCube adequately represented clouds of icons corresponding to sets of users' preferable tunes in the 2D cubic space.”
Figure 18. Bogdan Soban, Plant 1_1
Satoko Shiroi, Kazuo Misue, & Jiro Tanaka (2011, pp. 176-181) present “A Tool to Support Finding Favorite Music by Visualizing Listeners' Preferences.” The authors state, “In recent years, music-finding services have been increasing. If we have explicit information specifying pieces of music, we can find music to our taste using such services. This paper describes a tool to support music discovery. The tool visualizes a relational structure among music genres and the music-preference data of many listeners to make the users aware of their favorite music without explicit information. A case study is described to illustrate the usefulness of the tool.”
Barthes, R. (1964). Image, Reason, Déraison. Ed Barthes et al. L’universe de l’encyclopédie images d’une civilization. Les 135 plus belles planches de ‘encyclopédie de Diderot et d’Alambert. Paris: Les Libraires Assoiés.
Bertschi, S. (2007). Without Knowledge Visualization? Proposing a Deconstructivist Approach to Metaphor, Meaning and Perception. 11th International Conference on Information Visualization, Zurich, Switzerland (pp. 342-347). IEEE Computer Society Press.
Bertschi, S., Bresciani, S., Crawford, T., Goebel, R., Kienreich, W., Lindner, M., Sabol, V., & Moere, A.V. What is Knowledge Visualization? Perspectives on an Emerging Discipline. Proceedings of the Information Visualisation 15th International Conference, pp. 329-336. London. ISBN 978-1-4577-0868-8.
Also, retrieved December 2, 2011, from http://ieeexplore.ieee.org/
Bresciani, S., Eppler, M., Kaul, A., Ylinen, R. (2011). The Effectiveness of Knowledge Visualization for Organizational Communication in Europe and India. Proceedings of the 15th International Conference on Information Visualization, London, pp. 365-370. ISBN 978-1-4577-0868-8
Burgin, M. (2001). How We Know What Technology Can Do. In Communications of the ACM 44(11), 82-88.
Burgin, M. (1990). Theory of Named Sets as a Foundational Basis for Mathematics. In Structures in Mathematical Theories, pp. 417-420. San Sebastian.
Burkhard, R. (2005). Knowledge Visualization: The Use of Complementary Visual Representations for the Transfer of Knowledge – A Model, a Framework, and Four New Approaches. D.Sc. thesis, Swiss Federal Institute of Technology (ETH Zurich).
Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999). Information Visualization: Using Vision to Think. San Francisco, California: Morgan-Kaufmann.
Dinh Quyen Nguyen, Tominski, C., Schumann, H., & Tuan Anh Ta. (2011). Visualizing Tags with Spatiotemporal References. Proceedings of the 15th International Conference on Information Visualization, pp. 32-39. ISBN: 978-1-4577-0868-8.
Eden, C., & Ackermann, F. (2006). Where Next for Problem Structuring Methods. Journal of the Operational Research Society, 57(7), 766-768.
Edmonds, E. (2011). Art, Interaction and Engagement. Proceedings of the 15th International Conference on Information Visualization, London, pp. 451-456. ISBN 978-1-4577-0868-8
Elkins, J. (1999). The Domain of Images. Ithaca and London: Cornell U. Press.
Enterprise 2.0: Building Social Business (2011). Retrieved November 23, 2011, from http://www.e2conf.com
Eppler, M. J., & Burkhard, R. A. (2004). Knowledge Visualization. Towards a New Discipline and its Fields of Application. In Schwartz, D. G. (Ed.), Encyclopedia of Knowledge Management. Idea Group.
Eppler, M. J., & Burkhard, R. A. (2007). Visual Representations in Knowledge Management: framework and cases. Journal of Knowledge Management, 4(11), 112-122.
Eppler, M. J. (2011). What is an Effective Knowledge Visualization? Insights from a Review of Seminal Concepts. Proceedings of the 15th International Conference on Information Visualization, London, pp. 349 – 354. ISBN 978-1-4577-0868-8.
Eriksson, Y., & Johansson, P. (2011). Showing Action in Pictures. Proceedings of the 15th International Conference on Information Visualization, pp. 403-408. ISBN 978-1-4577-0868-8.
Fernstad, S. J., & Johansson, J. (2011). A Task Based Performance Evaluation of Visualization Approaches for Categorical Data Analysis. Proceedings of the 15th International Conference on Information Visualization, London, pp. 80-89. ISBN 978-1-4577-0868-8.
Friendly, M., & Denis, D. J. (2004), Milestones in the history of thematic cartography, statistical graphics, and data visualization. Web document, Retrieved November 9, 2010 from http://www.datavis.ca/gallery/. Also, http://datavis.ca/milestones/
Gebhardt, S., Meixner, C., & Burkhard, R. A. (2011). Distributed Group Collaboration in Interactive Applications. Proceedings of the 15th International Conference on Information Visualization, pp. 355-358. ISBN 978-1-4577-0868-8.
Geroimenko, V. (2011). Digital Photo Painting as an Artistic and Cultural Phenomenon. Proceedings of the 15th International Conference on Information Visualization, pp. 461-464. ISBN 978-1-4577-0868-8.
Gibson, J. J. (1986). The Ecological Approach to Visual Perception. Hillsdale, NJ: Lawrence Erlbaum Associates, 51.
Gkoutzis, K., & Geroimenko, V. (2011). Moving from Folksonomies to Taxonomies: Using the Social Web and 3D to Build an Unlimited Semantic Ontology. Proceedings of the 15th International Conference on Information Visualization, London, pp. 205-210. ISBN 978-1-4577-0868-8.
Haapio, H. (2011). Contract Clarity through Visualization -- Preliminary Observations and Experiments. Proceedings of the 15th International Conference on Information Visualization, London, pp. 337-342. ISBN 978-1-4577-0868-8.
Hakia, Leading Semantic Search Technology (2010). Retrieved November 23, 2011, from http://www.hakia.com/
Haudan, J., (2008). Visual Engagement helps transform solution selling. Marketing Times, September 2008 Edition. Sales & Marketing Executives International http://www.smei.org. Also, retrieved November 23, 2011, from http://www.rootlearning.com/wp-content/files_mf/1286464579MarketingTimesReprint_Sept_2008.pdf
Hockney, D. (2001). Secret Knowledge: Rediscovering the Lost Techniques of the Old Masters. Thames and Hudson, UK.
Hoffmann, H. G. M. (2003). Peirce’s “Diagrammatic Reasoning” as a Solution of the Learning Paradox. Process Pragmatism: Essays on Quiet Philosophical Revolution. Guy Debrock (Ed.), Amsterdam: Rodopi, pp. 121-143.
Information Visualization Proceedings. (2011). Retrieved December 1, 2011, from http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6003377 Proceedings of the Information Visualisation 15th International Conference. London. ISBN 978-1-4577-0868-8.
Johnson, S. (2011). Where good ideas come from. Retrieved November 23, 2011, from http://www.youtube.com/watch?v=NugRZGDbPFU
Kernbach, S., & Eppler, M. J. (2010). The Use of Visualization in the Context of Business Strategies: An Experimental Evaluation. Proceedings of the Information Visualisation (IV) 14th International Conference, London, pp. 349-354. ISBN 978-1-4244-7846-0.
Kerren, A., Prangova, M., & Paradis, C. (2011). Visualization of Sensory Perception Descriptions. Proceedings of the Information Visualisation (IV) 14th International Conference, London, pp. 135-144. ISBN 978-1-4244-7846-0.
Latour, B. (1990). Visualization and Cognition: Drawing Things Together. Lynch, M. & Woolgar, S. (Eds.) Representation in Scientific Activity, Cambridge, Mass: MIT Press, pp. 19-68.
Lengler, R., & Eppler, M. J. (2007). Towards a Periodic Table of Visualization Methods for Management. Proceedings of the IASTED International Conference on Graphics and Visualization in Engineering (GVE’07), pp. 83-88. Retrieved November 23, 2011, from http://www.visual-literacy.org/periodic_table/periodic_table.html
Lucia, A., Sabin, J. E., & Jones, P. L. (2011). Memory, difference, and information: generative architectures latent to material and perceptual plasticity. Proceedings of the 15th International Conference on Information Visualization, pp. 379-388. London. ISBN 978-1-4577-0868-8.
Machida, W., & Itoh, T. (2011). Lyricon: A Visual Music Selection Interface Featuring Multiple Icons. Proceedings of the Information Visualisation 15th International Conference, pp. 145-150, London. ISBN 978-1-4577-0868-8.
Marchese, F. T. (2011). Exploring the Origins of Tables for Information Visualization. Proceedings of the Information Visualisation 15th International Conference pp. 395-402. London. ISBN 978-1-4577-0868-8.
Marquis, J., & Wyeld, T. (2011). The Contemporisation of Dante's Inferno. Proceedings of the 15th International Conference on Information Visualization, pp. 585-587. London. ISBN 978-1-4577-0868-8.
Masud, L., Valsecchi, F., Ciuccarelli, P., Ricci, D., & Caviglia, G. (2010). From Data to Knowledge - Visualizations as Transformation Processes within the Data-Information-Knowledge Continuum. Proceedings of the 14th International Conference on Information Visualization, pp. 445-449. ISBN 978-1-4244-7846-0.
Morville, P. (2010). Experience Maps: KM and Visual Thinking, Presentation http://www.slideshare.net/ http://www.slideshare.net/morville/xmaps-upload presentation about visual thinking.
Norwich, K. H. (2003). Information, Sensation, and Perception. Originally published San Diego, CA: Academic Press; published on the Internet by Biopsychology.org 9.
Pidcock, W., & Uschold, M. (2003). What are the differences between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model? Retrieved November 23, 2011, from http://infogrid.org/trac/wiki/Reference/PidcockArticle.
Pombinho, P., Afonso, A. P., & Carmo, M. B. (2011). Chameleon – A Context Adaptive Visualization Framework for a Mobile Environment. Proceedings of the 15th International Conference on Information Visualization, pp. 151-157. London. ISBN 978-1-4577-0868-8.
Rusu, A., DiNicolantonio, S., Russell, R., & Velte, E. (2011). Abstract Camera Controller for Three-Dimensional Visualizations. Proceedings of the 15th International Conference on Information Visualization, pp. 434-439, London. ISBN 978-1-4577-0868-8.
Rusu, A., Fabian, A. J., Jianu, R., & Rusu, A. (2011). Using the Gestalt Principle of Closure to Alleviate the Edge Crossing Problem in Graph Drawings. Proceedings of the 15th International Conference on Information Visualization, pp. 488-493, London. ISBN 978-1-4577-0868-8.
Saito, Y. & Itoh, T. (2011). MusiCube: A Visual Interface for Music Selection Featuring Interactive Evolutionary Computing. Proceedings of the Information Visualisation 15th International Conference. London, p. 426. ISBN 978-1-4577-0868-8.
Sasakura, M., Kotaki, A., & Inada, J. (2011). A 3D Molecular Visualization System with Mobile Devices. Proceedings of the 15th International Conference on Information Visualization, pp. 429-433, London. ISBN 978-1-4577-0868-8.
Schmitt, G. (2009). Data Visualization is Reinventing Online Storytelling – and Building Brands in Bits and Bites. AdvertisingAge, AdAge Digital 19 March. Retrieved December 1, 2011, from http://adage.com/article/digitalnext/data-visualization-reinventing-online-storytelling/135313/
Segel, E., & Heer, J. (2010). Narrative Visualization. Telling Stories with Data. IEEE Transactions on Visualization and Computer Graphics 16(6), 1139-1148.
Shiroi, S., Misue, K., & Tanaka, J. (2011). A Tool to Support Finding Favorite Music by Visualizing Listeners' Preferences. Proceedings of the Information Visualisation 15th International Conference, pp. 176-181, London. ISBN 978-1-4577-0868-8.
Shneiderman, B. (1996). The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. Proceedings of the IEEE Symposium on Visual Languages (VL 96), pp. 336-343.
Silva, I.C., & Freitas, C.M. (2011). Using Visualization for Exploring Relationships between Concepts in Ontologies. Proceedings of the 15th International Conference on Information Visualization, pp. 317-322, London. ISBN 978-1-4577-0868-8.
Suthers, D. D. (2001). Towards a Systematic Study of Representational Guidance for Collaborative Learning Discourse. Journal of Universal Computer Science (J.UCS) 7(3), 254-277.
Swoogle, Semantic Web Search (2007). Retrieved November 23, 2011, from http://swoogle.umbc.edu/
Thomas, J. J., & Cook, K. A. (2006). A Visual Analytics Agenda. IEEE Computer Graphics and Applications, 26(1), 10-13.
Tufte, E. R. (1997). Visual Explanations. Cheshire, CT: Graphics Press.
Voigt, R. (2002), An extended scatterplot matrix and case studies in information visualization. Unpublished Masters thesis. Virtual Reality and Visualization Research Center, Vienna, AU.
Weber, W., & Tille, R. (2011). Listening to Managers: A Study about Visualizations in Corporate Presentations. Proceedings of the Information Visualisation 15th International Conference, pp. 343-348. London. ISBN 978-1-4577-0868-8.
Wei, H., Liu, E., Zhao, X, McFarlane, N. J. B., & Clapworthy, G. J. (2011). Web-Based 3D Visualisation for Biomedical Applications. Proceedings of the Information Visualisation 15th International Conference, pp. 632-637. London. ISBN 978-1-4577-0868-8.
Wyeld, T. (2011). The Implications of David Hockney's Thesis for 3D Computer Graphics. Proceedings of the Information Visualisation 15th International Conference, pp. 409-413, London. ISBN 978-1-4577-0868-8.
Zellweger, H. P. (2011). A Knowledge Visualization of Database Content Created by a Database Taxonomy. Proceedings of the Information Visualisation 15th International Conference pp. 323-328. London. ISBN 978-1-4577-0868-8.
Dr. Anna Ursyn is a Professor and Computer Graphics Area Head at the School of Art and Design, University of Northern Colorado. She had over 30 single juried and invitational art shows and participated in over 100 fine art exhibitions. Her articles and artwork have been published in books and journals. Research and pedagogy interests include integrated instruction in art, science, and computer art graphics. Liaison, Organizing and Program Committee member of IEEE Conferences on Information Visualization – iV: London, UK, and Computer Graphics, Imaging and Visualization Conferences – CGIV. Chair of the Symposium and Digital Art Gallery – D-ART iV.
Dr. Ebad Banissi is a Research Professor of Computer Graphics & Visualization, at the South Bank University, London, UK, and Director of Visualization & Graphics Research Unit – VGRU. Research and pedagogy interests include computer graphics anand visualization applications, in particular rendering, information visualization, graphics and 3D Web presence, forensic digital imaging, and computer animation. Author of many publications, initialized and since 1997 chairs the iV, IEEE Conferences on Information Visualization at the University of London, England, http://www.graphicslink.co.uk and CGIV Computer Graphics, Imaging and Visualization Conferences. He is involved in a large number of SME Research & Development projects.